diff --git a/models.py b/models.py
index 3968b726..dc008ada 100755
--- a/models.py
+++ b/models.py
@@ -114,16 +114,17 @@ class YOLOLayer(nn.Module):
             if cfg.endswith('yolov3-tiny.cfg'):
                 stride *= 2
 
-            ng = (int(img_size[0] / stride), int(img_size[1] / stride))  # number grid points
-            create_grids(self, max(img_size), ng)
+            nx = int(img_size[1] / stride)  # number x grid points
+            ny = int(img_size[0] / stride)  # number y grid points
+            create_grids(self, max(img_size), (nx, ny))
 
     def forward(self, p, img_size, var=None):
         if ONNX_EXPORT:
             bs = 1  # batch size
         else:
             bs, ny, nx = p.shape[0], p.shape[-2], p.shape[-1]
-            if (self.ny, self.nx) != (ny, nx):
-                create_grids(self, img_size, (ny, nx), p.device)
+            if (self.nx, self.ny) != (nx, ny):
+                create_grids(self, img_size, (nx, ny), p.device)
 
         # p.view(bs, 255, 13, 13) -- > (bs, 3, 13, 13, 85)  # (bs, anchors, grid, grid, classes + xywh)
         p = p.view(bs, self.na, self.nc + 5, self.ny, self.nx).permute(0, 1, 3, 4, 2).contiguous()  # prediction
@@ -238,8 +239,8 @@ def get_yolo_layers(model):
     return [i for i, x in enumerate(a) if x]  # [82, 94, 106] for yolov3
 
 
-def create_grids(self, img_size, ng, device='cpu'):
-    ny, nx = ng  # x and y grid size
+def create_grids(self, img_size=416, ng=(13, 13), device='cpu'):
+    nx, ny = ng  # x and y grid size
     self.img_size = img_size
     self.stride = img_size / max(ng)